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Individual-Based Modeling of Bacterial Foraging with Quorum Sensing in a Time-Varying Environment

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Evolutionary Computation,Machine Learning and Data Mining in Bioinformatics (EvoBIO 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4447))

Abstract

“Quorum sensing” has been described as “the most consequential molecular microbiology story of the last decade” [1][2]. The purpose of this paper is to study the mechanism of quorum sensing, in order to obtain a deeper understanding of how and when this mechanism works. Our study focuses on the use of an Individual-based Modeling (IbM) method to simulate this phenomenon of “cell-to-cell communication” incorporated in bacterial foraging behavior, in both intracellular and population scales. The simulation results show that this IbM approach can reflect the bacterial behaviors and population evolution in time-varying environments, and provide plausible answers to the emerging question regarding to the significance of this phenomenon of bacterial foraging behaviors.

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Elena Marchiori Jason H. Moore Jagath C. Rajapakse

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Tang, W.J., Wu, Q.H., Saunders, J.R. (2007). Individual-Based Modeling of Bacterial Foraging with Quorum Sensing in a Time-Varying Environment. In: Marchiori, E., Moore, J.H., Rajapakse, J.C. (eds) Evolutionary Computation,Machine Learning and Data Mining in Bioinformatics. EvoBIO 2007. Lecture Notes in Computer Science, vol 4447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71783-6_27

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  • DOI: https://doi.org/10.1007/978-3-540-71783-6_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71782-9

  • Online ISBN: 978-3-540-71783-6

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